1) Field of Invention
The present invention pertains generally to the field of spectrum analysis, and more particularly to the field of compact graphical representations of time-varying spectra. The invention is rooted in the field of speech analysis and speech parameter display.
2) Description of Prior Art
A series of devices were developed during the Second World War which may collectively be termed the sound spectrograph. Such devices were the first to automatically plot energy versus frequency over successive short-time intervals and were of particular value in the study of speech patterns. Frequency is plotted in the ordinate proceeding from zero frequency at the bottom to high frequency at the top, time is plotted in the abscissa proceeding from left to right as in printed matter, and energy is represented by the darkness in the plot at any given point. The resulting graphical format is compact in the space-filling sense of the term, and in principle all of the magnitude spectrum information is retained. There also exist real-time sound spectrographs which show a succession of such plots over time, as though a window of fixed temporal width were being swept across a wider static plot.
In another area of speech analysis the object is to transcribe speech into a sequence of symbols, i.e. discrete graphical entities typified by alphabetical characters, in which the transcription is based upon the so called phonemes of a language. The complexity of the output is preferred to be approximately that of a phonetic transcription as would be provided by a trained listener, will allophonic variations possibly indicated by the presence or absence of certain additional marks in the vicinity of the symbol. The resulting graphical format is considerably more compact than that of the sound spectrograph, but due to categorizing processes not all of the magnitude spectrum information is retained. Compactness in the abstract is gained while compactness in the space-filling sense of the term is lost.
Due to an obvious incompatibility with symbol strings as are used to represent the phoneme sequences of actual languages, the equation of single short-time spectra with single symbols has gone essentially unstudied. It will be seen, however, that such an equation does indeed carry validity in the context of time-varying output, and that a proper choice of transform allows retention of all magnitude spectral data as well as retention of the space-filling type of compactness. It is an object of the present invention to provide a symbolic continuum in which instantaneous variations in shape reflect instantaneous variations in the magnitude spectrum.
A third area of speech analysis in which the descriptions are remarkably compact is known as linear predictive coding. LPC is a group of digital signal processing techniques which were developed in the early nineteen seventies and which remain the most compact parametric mathematics known for the problem. LPC allows the rapid and efficient decomposition of speech signals into an all-pole transfer function which represents the filtering characteristics of the vocal tract, and a source function which regenerates the original speech signal when passed through the filter so derived. Magnitude spectrum information is thrown out when the LPC source function is represented incompletely, for example with the parameters system gain, periodicity versus randomness, and pitch when necessary. It is the algebraic or parametric nature of the complex polynomial form which is most central to the compactness of LPC representations, and one may thus refer to an algebraic or parametric type of compactness. It is an object of the present invention to allow the compact representation of unordered sets of complex numbers as single symbols, the compact representation of unordered sets of real numbers as single symbols, and the compact representation of single points in confined multidimensional subspaces as single symbols.
There are very many potential uses for such systems. Although the inputs are generally thought of as audio signals derived from microphones or from audio reproduction equipment, any electrical wave of analog origin having time-varying spectral content may substitute; an efficient representation will result as long as the frequency range has been shifted to that of audio. In many areas of science the raw data that results from an experiment consists of an electrical signal having time-varying spectral content, and so the first applications to be mentioned are in the viewing of data gathered during the course of physical experiments. Analysis of data from any region of the electromagnetic spectrum may be performed after an appropriate shifting of frequencies. The benefit over current spectrum analysis methods is that temporal relationships are placed in clearer evidence. To the experimenter, time becomes time. TVS may be used as a tool for performing a preliminary search of the data, and in certain situations its use may be appropriate in the final description.
A prime example of the need to place temporal relationships in clearer evidence is to be found in speech science. Coarticulation is said to be a set of exceptions to a set of rules, but coarticulation is the rule and not the exception. The use of an instrument that is suited to tracking acoustic phenomena over time can shed new light on the complex problems underlying the description of coarticulation. Filtering operations may be perfomed on the input in order to highlight the importance of specific formant trajectories, fricative resonances, plosive transients, or transitions between voicing and frication. The resulting graphical comparisons may be used in teaching of linguistics and foreign language skills, with students having the opportunity to approximate the images using their own voice. For speech-impaired individuals including the deaf, the time-varying symbol may offer a therapeutic option that is highly reliable and trustworthy, from the point of view of the student. Students may be struck by the reproducibility of their own results and seek to pursue the course of learning.